Expanding our fundamental knowledge of gene-proximal regions to improve selection models

Context and challenges

Transcription, the first stage of gene expression and protein synthesis, is tightly regulated by a number of molecular elements. Cis-regulatory elements, which consist of short DNA sequences, regulate gene expression via trans-acting factors that bind to the cis-regulatory elements.

Modifying gene expression through regulators

Cis-regulatory sequences are present in high density in the proximal regions of genes, but their characterization, an essential prerequisite for their use, remains incomplete. Recent projects have mapped DNA sequences preferentially located (known as PLMs) in these regions (in Arabidopsis thaliana and maize), with nearly 80% still unassigned in databases, although some are supported by MNase-defined cistrome occupancy analyses. Additionally,, numerous studies have shown that transposable elements (TEs) can include cis-regulatory sequences. When TEs are inserted near a gene, they can then affect the transcription of neighbouring genes by recruiting additional trans factors.

These two data sources (PLMs and TEs) are promising as they allow for the large-scale characterization of potential cis-regulatory elements. However, to gain a true understanding of proximal regions, these structural data need to be coupled with expression data. Original approaches using artificial intelligence may offer a promising way to integrate these biological data, thereby enabling the prediction of key genes and their regulatory networks. 

However, there are few opportunities for teams of experts working in these areas to come together with their different and complementary skills. The PRECURSOR consortium was therefore established to overcome this obstacle by creating an interdisciplinary network of experts to address this topic.

Goals

PRECURSOR will bring together scientific teams working at the interface between biology (molecular science, genetics, physiology) and formal science (statistics, computer science, bioinformatics), to investigate different species (maize, wheat, sorghum) and gain a consolidated vision of the genetic basis for traits of agronomic interest that will encompass both structural and expression data. 

The aim is to collaboratively advance the mapping and predictive power of cis-regulatory elements in the proximal regions of genes, taking into account the overall complexity of the question and the complementarities/differences between the species studied.

PRECURSOR’s main objective is to form an interdisciplinary scientific consortium based on the unprecedented integration of heterogeneous data to gain a better understanding of the proximal regions of genes and ultimately to develop new alleles of agronomic interest and improve the predictive power of selection models.

Contact-coordination

Project participants

INRAE structures

Non-INRAE partners